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Retrieving crop leaf area index by assimilation of MODIS data into a crop growth model

Science china Earth Sciences 2010年第5期53卷 721-730页

作者： WANG DongWei1,2,3, WANG JinDi1,2 & LIANG ShunLin4 1 State key laboratory of remote sensing Science, Jointly Sponsored by beijing normal university and Institute of remote sensing Applications, CAS, beijing 100875, china 2.school of geography, beijing key laboratory of environmental remote sensing and digital city, beijing normal university, beijing 100875, china 3 Haihe River Water Conservancy Commission, Tianjin 300170, china 4 Department of geography, university of Maryland, College Park, MD 20742, USA 1. State key laboratory of remote sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications CAS Beijing 100875 China2. School of Geography Beijing Key Laboratory of Environmental Remote Sensing and Digital City Beijing Normal University Beijing 100875 China3. Haihe River Water Conservancy Commission Tianjin 300170 China4. Department of Geography University of Maryland College Park MD 20742 USA

Leaf area index (LAI) is an important parameter in monitoring crop growth. One of the methods for retrieving LAI from remotely sensed observations is through inversion of canopy reflectance models. Many model inversion methods fail to account for variable LAI values at different crop growth stages. In this research, we use the crop growth model to describe the LAI changes with crop growth, and consider a priori LAI values at different crop growth stages as constraint information. The key approach of this research is to assimilate multiple canopy reflectance values observed at different growth stages and a priori LAI values into a coupled crop growth and radiative transfer model sequentially using a variational data assimilation algorithm. Adjoint method is used to minimize the cost function. Any other information source can be easily incorporated into the inversion cost function. The validation results show that the time series of MODIS canopy reflectance can greatly reduce the uncertainty of the inverted LAI values. Compared with MODIS LAI product at Changping and Shunyi Counties of beijing, this method has significantly improved the estimated LAI temporal profile.

关键词： inversion leaf area index crop growth model time series MODIS

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Development of environmental monitoring satellite systems in china

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Science china Earth Sciences 2010年第S1期53卷 1-7页

作者： LI GuoPing1 & CAO ChunXiang2 1 school of Earth and Space Sciences,Peking university,beijing 100871,china 2 State key laboratory of remote sensing Science,Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of Sciences and beijing normal university,beijing 100101,china 1. school of Earth and Space Sciences Peking University Beijing 100871 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China

With the increase in global environmental problems,the necessity and urgency of remote sensing technology being applied to environmental monitoring has been widely recognized around the *** has launched the environment and disaster monitoring and forecasting small satellite constellation HJ-1A/B and the FY3 atmosphere and environmental satellite,but they still cannot fully satisfy requirements for environmental *** paper summarizes the current status of satellite environmental monitoring in china and the existing problems of inadequate load design and low data utilization efficiency,and discusses the demand for environmental monitoring *** on the development of foreign satellite systems for environmental monitoring,the future development and key tasks of the environmental monitoring satellite system in china is discussed,as are some related initiatives.

关键词： environmental satellite environmental monitoring global climate change specialty load satellite system

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Effective solutions to a global 3D visual system in networking environments

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Science china Earth Sciences 2005年第11期48卷 2032-2039页

作者： ZHANG Liqiang1,2, ZHANG Yan3, YANG Chongjun2, LIU Suhong1, REN Yingchao2, RUI Xiaoping2 & LIU Donglin2 1. State key laboratory of remote sensing Sciences, school of geography and remote sensing, beijing normal university, beijing 100875, china 2. State key laboratory of remote sensing Sciences, Institute of remote sensing Applications, Chinese Academy of Sciences, beijing 101001, china 3. Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, beijing 101001, china 1. State key laboratory of remote sensing Sciences School of Geography and Remote Sensing Beijing Normal University 100875 Beijing China 2. Chinese Academy of Sciences State Key Laboratory of Remote Sensing SciencesInstitute of Remote Sensing Applications 101001 Beijing China 3. Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences 101001 Beijing China

The development of Web-based global 3D visual system has made progresses. However, there exist few mature and effective ways for managing, transmitting and visualizing massive spatial data. Based on the related work, the paper illustrates the ellipsoidal quadtree technique for rapid access multi-scale and multiple level geographical data, integrates the streaming with level-of-detail rendering method for transmitting the data on the network, and im-plements large-scale terrain surface simplification using M-band wavelet transforms and mul-tiresolution triangulations. We fulfil a web-based global terrain visual system using COM com-ponents on the basis of the above techniques. The system has a good prospect in the military simulation and city plans.

关键词： massive spatial data, streaming transmission, system architecture, M-band wavelet

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Study on Water Consumption Coefficient of People's Living and Its Regional Disparity in the North of china

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Chinese Journal of Population,Resources and Environment 2005年第2期3卷 20-26页

作者： Wang Jing’ai 1-3, Mao Rui 3,4, Yang Mingchuan 3,4 & Zhou Junju 11 College of geography & remote sensing 2 key laboratory of Regional geography of beijing normal university 3 key laboratory of environmental Change and Natural Disaster of Ministry of Education of china 4 College of Resources Science & Technology, beijing normal university, beijing 100875, china College of geography and remote sensing Beijing 100048 China key laboratory of environmental Change and Natural Disaster of Ministry of Education of china Beijing 100048 China College of Resources Science and Technology Beijing Normal University Beijing 100875 China

By employing the information-reshufflingmethod that integrates census data, precipitation dataand inquiry data of water consumption, this paperdiscusses 5 (water consumption coefficient of people’sliving) in allusion to different precipitation zones anddifferent periods of time. The study shows that 5-(water consumption coefficient of urban people’sliving), 5. (water consumption coefficient of ruralpeople’s living) and increase with time passing, andthe increasing extent of 5 is 1.84, 2.62, 2.84 and 2.68times respectively from the west to the east, whichresults from the total quantity of water resources andthe speed of urbanization. 5- and 5. of eachprecipitation zone increased with 5- increasing morequickly than 5., and the difference between the twoalso increased when time passed. In the past fifty years(1950-2000), the increasing extent of 5- was 1.71,2.96, 2.41 and 2.33 times respectively from the westto the east, in which 200-400mm precipitation zoneincreased more than others. Meanwhile the increasingextent of 5. is 1.55, 1.60, 1.53 and 1.64 timesrespectively from the west to the east with eachprecipitation zone increasing similarly. The change of5-is due to the speed of urbanization and the stabilityof water resources. This study provides basis forcalculating the water demand of people’s living andrevealing the impact of water demand of people’s livingon ecological drought in different zones.

关键词： The north of china precipitation zone water consumption coefficient of people’s living

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Principle of small target detection for hyperspectral imagery

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Science china Earth Sciences 2007年第8期50卷 1225-1231页

作者： GENG XiuRui1,2,3 & ZHAO YongChao2,3,4 1 Research Center for remote sensing and GIS, Department of geography, beijing normal university, beijing 100875, china 2 State key laboratory of remote sensing Science, Chinese Academy of Sciences, beijing 100101, china 3 Institute of Erectronics, Chinese Academy of Sciences, beijing 100080, china 4 Center for for Assessment and Monitoring of Forest and environmental Resources and Division of Ecosystem Sciences university of California Berkeley, CA 94720-3114, USA 1. Research Center for remote sensing and GIS Department of Geography Beijing Normal University Beijing 100875 China 2. State key laboratory of remote sensing Science Chinese Academy of Sciences Beijing 100101 China 3. Institute of Erectronics Chinese Academy of Sciences Beijing 100080 China 4. Center for for Assessment and Monitoring of Forest and environmental Resources and Division of Ecosystem Sciences University of California Berkeley CA 94720-3114 USA

This paper generalizes the progress of algorithms in small target detection for hyperspectral imaging, and finds that whitening the image is the key point of many methods in small target detection. An al-gorithm is presented to detect desired targets by converting large targets into small ones based on the weighted sample autocorrelation matrix.

关键词： hyperspectral whiten target detection

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Scale effects of leaf area index inversion based on environmental and disaster monitoring satellite data

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Science china Earth Sciences 2010年第S1期53卷 92-98页

作者： ZHANG Hao1,LI XiaoWen1,2,CAO ChunXiang1,YANG Hua2,GAO MengXu1,3,ZHENG Sheng1,3,XU Min1,3,XIE DongHui2,JIA HuiCong1,JI Wei1,ZHAO Jian1,3,CHEN Wei1,3 & NI XiLiang1,3 1 State key laboratory of remote sensing Science,Jointly Sponsored by Institute of remote sensing Applications,Chinese Academy of Sciences and beijing normal university,beijing 100101,china 2 State key laboratory of remote sensing Science,Jointly Sponsored by beijing normal university and Institute of remote sensing Applications of Chinese Academy of Sciences,beijing 100875,china 3 Graduate university of Chinese Academy of Sciences,beijing 100049,china 1. State key laboratory of remote sensing Science Jointly Sponsored by Institute of Remote Sensing Applications Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China2. State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications of Chinese Academy of Sciences Beijing 100875 China3. Graduate University of Chinese Academy of Sciences Beijing 100049 China

The spatial distribution of sub-pixel components has an impact on retrieval accuracy,and should be accounted for when inverting a three-dimensional adiative transfer model to retrieve leaf area index(LAI).To investigate this effect,we constructed three realistic scenarios with the same LAI values and other properties,except that the simulated plants had different *** implemented the radiosity method to subsequently produce synthetic bidirectional reflectance factor(BRF) datasets based upon these simulated *** inversion was conducted using these data,which showed that spatial distribution affects retrieval *** inversion was also conducted for LAI based on charge-coupled device(CCD) data from the Environment and Disaster Monitor Satellite(HJ-1),which depicted both forest and drought-resistant crop land *** showed that heterogeneity in coarse-resolution remote sensing data is the main error source in LAI *** spatial distribution of global fractal dimension index,which can be used to describe the area of sub-pixel components and their spatial distribution modes,shows good consistency with the coarse resolution LAI inversion error.

关键词： HJ-1 leaf area index scale effect spatial distribution

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Calculating soil moisture by remote sensing and analyzing hydrologic cycle process in the Yellow River basin

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Science china(Technological Sciences) 2004年第z1期47卷 1-13页

作者： YANG Shengtian1 & LIU Changming1, 2 1. school of environmental Sciences, beijing normal university, beijing 100875, china 2. Institute of Geographic Science and Natural Resources Research, beijing 100101, china beijing normal Univ Sch Environm Sci Beijing 100875 Peoples R China Inst Geog Sci & Nat Resources Beijing 100101 Peoples R China

Based on the AVHRR pathfinder remote sensing data, soil moisture, precipitation and evaporation during the period of 1982—1998, soil moisture of all layers of soil-profile (0—1 m) in the Yellow River basin over the 17 years are calculated by the remote sensing model of calculating soil water. The Yellow River basin is divided into seven subcatchments as control sections at the location of six hydrologic stations (Lanzhou, Toudaoguai, Longmen, Sanmenxia, Huayuankou and Lijin). After calculating soil moisture and obtaining runoff data and precipitation data, the dynamical features of hydrological cycle in the Yellow River basin are analyzed for the period from 1982 to 1988 using water balance method. The conclusions are as follows: It is feasible to calculate the soil water on the macro-scale, in the soil profile with temporal continuity by means of remote sensing and survey in land. Some values of the key water cycle factors in the Yellow River are obtained, which include the annual precipitation of 4000 km3, the evapotranspiration of 3000-3500 km3, and the soil moisture transformation of ?500- 500 km3. Consequently, we analyzed the process of the water cycle in the Yellow River over the 17 years, and the results show that the segment upstream of Lanzhou city is a relatively humid region, and the area of internal waters and the reaches of Shanshan is the most desiccated region. Therefore, the runoff in the depth process is intensive and the runoff-generating process is weak in more arid regions.

关键词： the Yellow River, soil moisture, remote sensing, hydrologic cycle.

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Spatial prediction and analysis of Himalayan marmot plague natural epidemic foci in china based on HJ-1 satellite data

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Science china Earth Sciences 2010年第S1期53卷 8-15页

作者： GAO MengXu1,4,LI XiaoWen1,2,CAO ChunXiang1,ZHANG Hao1,LI Qun3,ZHOU Hang3 HE QiSheng1,4,XU Min1,4,ZHAO Jian1,4,ZHENG Sheng1,4 & CHEN Wei1,4 1State key laboratory of remote sensing Science,Jointly Sponsored by the Institute of remote sensing Applications of Chinese Academy of Sciences and beijing normal university,beijing 100101,china 2school of geography,beijing normal university,beijing 100875,china 3Office for Disease Control and Emergency Response,Chinese Center for Disease Control and Prevention,beijing 102206,china 4Graduate university of Chinese Academy of Sciences,beijing 100049,china 1. State key laboratory of remote sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China4. Graduate University of Chinese Academy of Sciences Beijing 100049 China2. School of Geography Beijing Normal University Beijing 100875 China3. Office for Disease Control and Emergency Response Chinese Center for Disease Control and Prevention Beijing 102206 China

Plague,caused by the gram-negative bacterium Yersinia pestis,is a serious and rapidly progressing illness in humans that can be fatal if not treated *** Qinghai-Tibet Plateau is the largest area of natural Himalayan marmot(Marmota himalayana) plague foci in china and covers more than 630000 *** County in Gansu Province is a part of this natural focus of plague and was chosen as a study *** study used an ecological niche modeling(ENM) approach to predict the potential distribution of the Himalayan *** and Disaster Monitor Satellite(HJ-1) data was used to investigate environment factors that affect plague host animal *** animal point data from active surveillance was combined with environmental variables from the HJ-1 satellite and other databases,and the models of the potential distribution of Himalayan marmot were produced with the Genetic Algorithm for Rule-Set Production(GARP).The probability of marmot presence was divided into 0-5%,5%-20%,20%-40%,40%-80%,and 80%-100% *** with 80%-100% probability exhibited the greatest potential for the presence of Himalayan *** to the predicted potential distribution of Himalayan marmot in the study area,active surveillance of plague hosts and plague control and prevention could be more efficient.

关键词： Himalayan marmot plague spatial prediction GARP HJ-1 satellite

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Spectral response of rice(Oryza sativa L.) leaves to Fe^(2+) stress

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Science china(Life Sciences) 2009年第8期52卷 747-753页

作者： CHI GuangYu1,2,CHEN Xin1,SHI Yi1 & LIU XinHui3 1 key laboratory of Terrestrial Ecological Process,Institute of Applied Ecology,Chinese Academy of Sciences,Shenyang 110016,china 2 Graduate school of Chinese Academy of Sciences,beijing 100049,china 3 State key Joint laboratory of environmental Simulation and Pollution Control,school of Environment,beijing normal university,beijing 100875,china key laboratory of Terrestrial Ecological Process Institute of Applied Ecology Chinese Academy of Sciences Shenyang 110016 China Graduate school of Chinese Academy of Sciences Beijing 100049 China State key Joint laboratory of environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing 100875 China

In the management of lake eutrophication,the regulation effect of Fe is considered,in addition to the controlling nitrogen-and phosphorus *** on the "Fe hypothesis",this paper tentatively applied plant spectral response to the remote sensing early-warning mechanism of lake eutrophication.A laboratory water culture experiment with rice(Oryza sativa L.) was conducted to study Fe uptake by plants and the chlorophyll concentration and visible-near infrared spectrum of vegetable leaves as well as their interrelations under Fe2+ *** spectral indices,i.e.,A1(integral value of the changes of spectral reflectivity in the range 460―670 nm under Fe2+ stress),A2(integral value of the changes of spectral reflectivity in the range of 760―1000 nm under Fe2+ stress) and S(blue-shift range of red edge curve under Fe2+ stress),were used to establish quantitative models about the relationships between the rice leaf spectrum and Fe2+ *** the increase of Fe2+ in a culture solution,the Fe content in rice plants increased,while the chlorophyll concentration in vegetative leaves *** spectral reflectivity of vegetable leaves increased in the visible light band but decreased in the near infrared band,and the blue-shift range of the red edge curve *** indices A1,A2 and S all had significant correlations with the Fe content in rice leaves,the correlation coefficient being respectively 0.951(P 0.96) and predict the Fe level in rice leaves.

关键词： rice(Oryza sativa L.) spectrum Fe2+ lake eutrophication

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Natural eco-environmental evaluation of eastern Qinghai-Tibet Plateau using RS and GIS

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Journal of Geographical Sciences 2002年第3期12卷 283-288页

作者： YANG Shengtian, LIU Changming, YANG Zhifeng, SUNRui, ZHOU Xiaodong(1. Inst. of environmental Sciences, beijing normal university, beijing 100875, china 2. Dept. of Resources and environmental Science, beijing normal university, beijing 100875,china) Inst. of environmental Sciences Beijing Normal University 北京 100875 Dept. of Resources and environmental Science Beijing Normal University 北京 100875

The impact of interbasin water transfer on environment is very significant. The affected area of the west route scheme of the South to North Water Transfer Project in china (SNWT) is located in the eastern Tibetan Plateau, where the altitude is high with frigid eco-environment. In this article, remote sensing and GIS are applied to analyze the natural environment and the natural environment index is established to express the natural conditions of the study area. After the natural environment index is divided into four grades and the features of each grade are analysed, some results are obtained for reference in environmental assessment of the west route of SNWT.

关键词： Qinghai-Tibet Plateau environmental assessment remote sensing GIS

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